Parametric modelling of prevalent cohort data with uncertainty in the measurement of the initial onset date

In prevalent cohort studies with follow-up, if disease duration is the focus, the date of onset must be obtained retrospectively. For some diseases, such as Alzheimer’s disease, the very notion of a date of onset is unclear, and it can be assumed that the reported date of onset acts only as a proxy for the unknown true date of onset. When adjusting for onset dates reported with error, the features of left-truncation and potential right-censoring of the failure times must be modeled appropriately. Under the assumptions of a classical measurement error model for the onset times and an underlying parametric failure time model, we propose a maximum likelihood estimator for the failure time distribution parameters which requires only the observed backward recurrence times. Costly and time-consuming follow-up may therefore be avoided. We validate the maximum likelihood estimator on simulated datasets under varying parameter combinations and apply the proposed method to the Canadian Study of Health and Aging dataset.

     

‘Just choose the easy option’: students talk about alcohol use and social influence

Previous research into young people’s drinking behaviour has studied how social practices influence their actions and how they negotiate drinking-related identities. Here, adopting the perspective of discursive psychology we examine how, for young people, social influences are bound up with issues of drinking and of identity. We conducted 19 focus groups with undergraduate students in Australia aged between 18 and 24 years. Thematic analysis of participants’ accounts for why they drink or do not drink was used to identify passages of talk that referred to social influence, paying particular attention to terms such as ‘pressure’ and ‘choice’. These passages were then analysed in fine-grained detail, using discourse analysis, to study how participants accounted for social influence. Participants treated their behaviour as accountable and produced three forms of account that: (1) minimised the choice available to them, (2) explained drinking as culture and (3) described resisting peer pressure. They also negotiated gendered social dynamics related to drinking. These forms of account allowed the participants to avoid individual responsibility for drinking or not drinking. These findings demonstrate that the effects of social influence on young people’s drinking behaviour cannot be assumed, as social influence itself becomes negotiable within local contexts of talk about drinking.     

A risk set adjustment for proportional hazards modeling of combined cohort data

Sporting careers observed over a preset time interval can be partitioned into two distinct subsamples. These samples consist of individuals whose careers had already commenced at the start of the time interval (prevalent subsample) and individuals whose careers began during the time interval (incident subsample) as well the respective individual-level covariate data such as salary, height, weight, performance statistics, draft position, etc. Under the assumption of a proportional hazards model, we propose a partial likelihood estimator to model the effect of covariates on survival via an adjusted risk set sampling procedure for when the incident cohort data is used in conjunction with the prevalent cohort data. We use simulated failure time data to validate the combined cohort proportional hazards methodology and illustrate our model using an NBA data set for career durations measured between 1990 and 2008.